Mammographic density in relation to breast cancer recurrence and survival in women receiving neoadjuvant chemotherapy

ObjectiveThe association between mammographic density (MD) and breast cancer (BC) recurrence and survival remains unclear. Patients receiving neoadjuvant chemotherapy (NACT) are in a vulnerable situation with the tumor within the breast during treatment. This study evaluated the association between MD and recurrence/survival in BC patients treated with NACT.MethodsPatients with BC treated with NACT in Sweden (2005–2016) were retrospectively included (N=302). Associations between MD (Breast Imaging-Reporting and Data System (BI-RADS) 5th Edition) and recurrence-free/BC-specific survival at follow-up (Q1 2022) were addressed. Hazard ratios (HRs) for recurrence/BC-specific survival (BI-RADS a/b/c vs. d) were estimated using Cox regression analysis and adjusted for age, estrogen receptor status, human epidermal growth factor receptor 2 status, axillary lymph node status, tumor size, and complete pathological response.ResultsA total of 86 recurrences and 64 deaths were recorded. The adjusted models showed that patients with BI-RADS d vs. BI-RADS a/b/c had an increased risk of recurrence (HR 1.96 (95% confidence interval (CI) 0.98–3.92)) and an increased risk of BC-specific death (HR 2.94 (95% CI 1.43–6.06)).ConclusionThese findings raise questions regarding personalized follow-up for BC patients with extremely dense breasts (BI-RADS d) pre-NACT. More extensive studies are required to confirm our findings

18F-FDG-PET/CT in breast cancer imaging: Restaging and Implications for treatment decisions in a clinical practice setting

Background and purpose: Although the diagnostic accuracy of 18F-fluorodeoxyglucose – positron emission tomography/computed tomography (18F-FDG-PET/CT) for breast cancer (BC) has been well studied, few studies have evaluated the impact of 18F-FDG-PET/CT on BC patient care. This study aimed to investigate restaging and 18F-FDG-PET/CT-induced changes in clinical decision-making in patients with BC. Material and methods: We retrospectively evaluated 18F-FDG-PET/CT-scans performed for BC-related indications in a prospectively collected consecutive cohort of adult patients at Skane University Hospital, Sweden. Patients with all BC stages were included and divided into three groups based on the indication for 18F-FDG-PET/CT: Group A (primary staging), Group B (response evaluation), and Group C (recurrence). The impact of 18F-FDG-PET/CT-scans on clinical management was categorized as no change, minor change (e.g. modification of treatment plans), or major change (e.g. shift from curative to palliative treatment intention). Results: A total of 376 scans (151 patients) were included: Group A 9.3% (35 of 376 scans), Group B 77.4% (291 of 376 scans), and Group C 13.3% (50 of 376 scans). Significant stage migration, predominantly upstaging, occurred in Group A (45.7%) and Group C (28.0%). Changes in clinical management were observed in 120 scans (31.9%), of which 66 were major and 54 were minor. The largest proportion of 18F-FDG-PET/CT-induced management changes were observed in Group A (57.1%), most commonly a shift from curative to palliative treatment intention due to upstaging. Interpretation: Our study indicates the clinical utility of 18F-FDG-PET/CT in BC restaging and changes in clinical management; the latter observed in approximately one-third of all cases

Mammographic density in relation to breast cancer recurrence and survival in women receiving neoadjuvant chemotherapy

Objective: The association between mammographic density (MD) and breast cancer (BC) recurrence and survival remains unclear. Patients receiving neoadjuvant chemotherapy (NACT) are in a vulnerable situation with the tumor within the breast during treatment. This study evaluated the association between MD and recurrence/survival in BC patients treated with NACT. Methods: Patients with BC treated with NACT in Sweden (2005–2016) were retrospectively included (N=302). Associations between MD (Breast Imaging-Reporting and Data System (BI-RADS) 5th Edition) and recurrence-free/BC-specific survival at follow-up (Q1 2022) were addressed. Hazard ratios (HRs) for recurrence/BC-specific survival (BI-RADS a/b/c vs. d) were estimated using Cox regression analysis and adjusted for age, estrogen receptor status, human epidermal growth factor receptor 2 status, axillary lymph node status, tumor size, and complete pathological response. Results: A total of 86 recurrences and 64 deaths were recorded. The adjusted models showed that patients with BI-RADS d vs. BI-RADS a/b/c had an increased risk of recurrence (HR 1.96 (95% confidence interval (CI) 0.98–3.92)) and an increased risk of BC-specific death (HR 2.94 (95% CI 1.43–6.06)). Conclusion: These findings raise questions regarding personalized follow-up for BC patients with extremely dense breasts (BI-RADS d) pre-NACT. More extensive studies are required to confirm our findings

Abstract P3-07-04: Effects of statin use on volumetric mammographic density: Results from the Karolinska mammography project for risk prediction of breast cancer (KARMA) study

Abstract Introduction: High mammographic density is an established risk factor for breast cancer, whereas epidemiological data on statins and breast cancer risk have been inconclusive. The aim of this study was to address the role of statins in breast cancer risk by studying their effect on mammographic density in a large screening-based cohort. Methods: The KARolinska MAmmography project for the risk prediction of breast cancer (KARMA) study includes 70,876 women who performed either a screening or clinical mammography from January 2011 to December 2013. In all, 41,102 women responded to a web-based questionnaire, and their raw digital mammograms were stored and their volumetric mammographic density was estimated using the Volpara™ system. Information on statin use was obtained through the Swedish National Prescription Register. Analysis of covariance was used to study the effect of current statin use on mammographic density, adjusting for a large set of potential confounders. Analyses were stratified by statin lipophilicity and exposure duration. The potential effect modification by hormone replacement therapy (HRT) was analyzed. Results: Statin use was recorded in approximately 3,300 women (8.1%) of the study population of 41,102, the majority of which was prescribed a lipophilic statin (93.4% of statin users). After multivariable adjustment, volumetric percent density was lower in statin users than in non-users (P&amp;lt;0.001). Further, statin users had a larger non-dense volume than non-users (P&amp;lt;0.001), but no difference in absolute dense volume was detected. No differential effects were observed according to lipophilicity of the statin or drug duration. Interaction analyses revealed effect modification by HRT (P-interaction=0.03) with statin use being associated with a larger dense volume among ever HRT users. Participant characteristicsTotalStatin useP valueNoYesN = 37,765N = 3,337Age (years)55.054.263.8&amp;lt; 0.001BMI (kg/m2)25.425.227.1&amp;lt; 0.001Menopausal status, % (N)&amp;lt; 0.001Premenopausal40.2 (16,506)43.1 (16,272)7.0 (234)Perimenopausal/unknown3.3 (1,349)3.5 (1,304)1.4 (45)Postmenopausal56.6 (23,247)53.5 (20,189)91.6 (3,058) Volumetric mammographic density measures by current statin use.Model 1Model 2Model 3Model 4Statin useVolumetric percent density (%)No8.017.937.937.94Yes6.897.737.747.66P value&amp;lt; 0.0010.0010.001&amp;lt; 0.001Dense volume (cm3)No56.857.157.157.0Yes60.757.657.558.0P value&amp;lt; 0.0010.310.320.06Statin typeVolumetric percent density (%)None8.017.937.937.94Lipophilic6.927.737.777.69Hydrophilic6.467.327.347.26P value&amp;lt; 0.001&amp;lt; 0.001&amp;lt; 0.001&amp;lt; 0.001Dense volume (cm3)None56.857.157.157.0Lipophilic60.857.757.758.1Hydrophilic58.255.054.855.3P value&amp;lt; 0.0010.200.660.21Model 1: adjusted for age Model 2: Model 1 + BMI Model 3: Model 2 + menopausal status, HRT use, parity, age at menarche, education level, smoking, alcohol consumption and benign breast disease Model 4: Model 3 + low-dose aspirin and metformin use Conclusions: Statin use was associated with a lower mammographic percent density, although no evidence was found for an effect of statins on absolute dense volume. The observed interaction between statin and HRT use requires further investigation. Citation Format: Ida Skarping, Judith Brand, Per Hall, Signe Borgquist. Effects of statin use on volumetric mammographic density: Results from the Karolinska mammography project for risk prediction of breast cancer (KARMA) study [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P3-07-04.</jats:p

Deep learning analysis of serial digital breast tomosynthesis images in a prospective cohort of breast cancer patients who received neoadjuvant chemotherapy

Purpose: Different imaging tools, including digital breast tomosynthesis (DBT), are frequently used for evaluating tumor response during neoadjuvant chemotherapy (NACT). This study aimed to explore whether using artificial intelligence (AI) for serial DBT acquisitions during NACT for breast cancer can predict pathological complete response (pCR) after completion of NACT. Methods: A total of 149 women (mean age 53 years, pCR rate 22 %) with breast cancer treated with NACT at Skane University Hospital, Sweden, between 2014 and 2019, were prospectively included in this observational cohort study (ClinicalTrials.gov: NCT02306096). DBT images from both the cancer and contralateral healthy breasts acquired at three time points: pre-NACT, after two cycles of NACT, and after the completion of six cycles of NACT (pre-surgery) were analyzed. The deep learning AI system used to predict pCR consisted of a backbone 3D ResNet and an attention and prediction module. The GradCAM method was used to obtain insights into the model decision basis through a quantitative analysis of the importance maps on the validation set. Moreover, specific model choices were motivated by ablation studies. Results: The AI model reached an AUC of 0.83 (95% CI: 0.63–1.00) (test set). The spatial correlation of importance maps for input volumes from the same patient but at different time points was high, possibly indicating that the model focuses on the same areas during decision-making. Conclusions: We demonstrate a high discriminative performance of our algorithm for predicting pCR/non-pCR. Availability of larger datasets would permit more comprehensive training of the models and more rigorous evaluation of their prediction performance for future patients

Effects of statin use on volumetric mammographic density: results from the KARMA study.

Epidemiological data on statins and breast cancer risk have been inconclusive. The aim of this study was to clarify the role of statins in breast cancer risk by studying their effect on mammographic density

Predicting pathological axillary lymph node status with ultrasound following neoadjuvant therapy for breast cancer

Purpose: High-performing imaging and predictive markers are warranted to minimize surgical overtreatment of the axilla in breast cancer (BC) patients receiving neoadjuvant chemotherapy (NACT). Here we have investigated whether axillary ultrasound (AUS) could identify axillary lymph node (ALN) metastasis (ALNM) pre-NACT and post-NACT for BC. The association of tumor, AUS features and mammographic density (MD) with axillary-pathological complete response (axillary-pCR) post-NACT was also assessed. Methods: The NeoDense-study cohort (N = 202, NACT during 2014–2019), constituted a pre-NACT cohort, whereas patients whom had a cytology verified ALNM pre-NACT and an axillary dissection performed (N = 114) defined a post-NACT cohort. AUS characteristics were prospectively collected pre- and post-NACT. The diagnostic accuracy of AUS was evaluated and stratified by histological subtype and body mass index (BMI). Predictors of axillary-pCR were analyzed, including MD, using simple and multivariable logistic regression models. Results: AUS demonstrated superior performance for prediction of ALNM pre-NACT in comparison to post-NACT, as reflected by the positive predictive value (PPV) 0.94 (95% CI 0.89–0.97) and PPV 0.76 (95% CI 0.62–0.87), respectively. We found no difference in AUS performance according to neither BMI nor histological subtype. Independent predictors of axillary-pCR were: premenopausal status, ER-negativity, HER2-overexpression, and high MD. Conclusion: Baseline AUS could, to a large extent, identify ALNM; however, post-NACT, AUS was insufficient to determine remaining ALNM. Thus, our results support the surgical staging of the axilla post-NACT. Baseline tumor biomarkers and patient characteristics were predictive of axillary-pCR. Larger, multicenter studies are needed to evaluate the performance of AUS post-NACT